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Developmental coordination disorder (DCD), also known as developmental motor coordination disorder, developmental dyspraxia, or simply dyspraxia (from Ancient Greek praxis 'activity'), is a neurodevelopmental disorder [1] characterized by impaired coordination of physical movements as a result of brain messages not being accurately transmitted to the body.
Developmental verbal dyspraxia (DVD), also known as childhood apraxia of speech (CAS) and developmental apraxia of speech (DAS), [1] is a condition in which an individual has problems saying sounds, syllables and words. This is not because of muscle weakness or paralysis.
There are two types of Apraxia. Developmental (or Childhood Apraxia of speech) or acquired Apraxia. Childhood apraxia of speech (CAS) is a neurological childhood speech sound disorder that involves impaired precision and consistency of movements required for speech production without any neuromuscular deficits (ASHA, 2007a, Definitions of CAS section, para. 1).
The Child and Adolescent Symptom Inventory (CASI) is a behavioral rating checklist created by Kenneth Gadow and Joyce Sprafkin that evaluates a range of behaviors related to common emotional and behavioral disorders identified in the Diagnostic and Statistical Manual of Mental Disorders (DSM), including attention deficit hyperactivity disorder, oppositional defiant disorder, conduct disorder ...
Developmental verbal dyspraxia (DVD), also known as childhood apraxia of speech (CAS) and developmental apraxia of speech (DAS), [3] [4] is an inability to utilize motor planning to perform movements necessary for speech during a child's language learning process. Although the causes differ between AOS and DVD, the main characteristics and ...
With improvements, children with apraxia may be transitioned into group therapy settings. Therapeutic exercises must focus on planning, sequencing, and coordinating the muscle movements involved in speech production. Children with developmental verbal dyspraxia must practice the strategies and techniques that they learn to improve.
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Achenbach used machine learning and principal component analysis when developing the ASEBA in order to cluster symptoms together when forming the assessment's eight categories. This approach ignored the syndrome clusters found in the DSM-I, instead relying on patterns found in case records of children with identified psychopathologies.